Published 8/2023
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 4.83 GB | Duration: 4h 48mMaster the data analysis and visualization libraries in Python: Numpy, Pandas, Matplotlib, Seaborn, Plotly + more
What you'll learnJupyter Notebooks IDE / Anaconda Distribution
Python, we will be using Python3 in this course
Data Analysis Libraries in Python such as NumPy and Pandas
Data Visualization Libraries in Python such as Matplotlib and Seaborn
A resume ready project
You will get to learn through the practical implementation
RequirementsBasic knowledge of python programming is needed
DescriptionLearn By Making Project which could be added in the resumeLearn one of the most in demand programming languages in the world and master the most important libraries when it comes to analyzing and visualizing data.This course can be split into 3 key areas:The first area of the course focuses on core Python3 and teaches you the essentials you need to be able to master the libraries taught in this courseThe second area focuses on analysing and manipulating data. You will learn how to master both NumPy and PandasFor the final part of the course you learn how to display our data in the form of interesting charts using Matplotlib, Seaborn and Plotly ExpressYou will be using Google colab, a cloud based IDE for writing the codes.The course is packed with lectures, code-along videos, coding exercises and quizzes.On top of that there are numerous dedicated challenge sections that utilize interesting datasets to enable you to make the most out of these external libraries.There should be more than enough to keep you engaged and learning! As an addition you will also have lifetime access to all the lectures as well as lots of downloadable course resources consisting of detailed Notebooks.The aim of this course is to make you proficient at using Python and the data analysis and visualization libraries.This course is suitable for students of all levels and it doesn't matter what operating system you use.
OverviewSection 1: Titanic dataset analysis
Lecture 1 Pclass vs survived vs gender class
Lecture 2 Introduction and importing of libraries
Lecture 3 Gathering information about the data
Lecture 4 Visualizing the data
Lecture 5 Featuring - gender class
Lecture 6 Survived class
Lecture 7 Featuring - Passenger class
Lecture 8 Plots for gender class
Lecture 9 visualizing other parameters
Lecture 10 Feature - Age class
Lecture 11 11
Lecture 12 12
Lecture 13 13
Lecture 14 14
Lecture 15 15
Lecture 16 16
Lecture 17 19
Lecture 18 27
Lecture 19 28
Lecture 20 29
Anyone interested in learning Python,Python developers curious about the data visualization libraries,Python developers curious about the data analysis libraries,Python developers curious about the data analysis libraries
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